1. Technical Field
In one aspect, the invention relates to a wireless communication system, a wireless communication apparatus, and a wireless communication method using spatial multiplexing, and more particularly, to a wireless communication system, a wireless communication apparatus, and a wireless communication method, in which a transmitter and a receiver share channel information to perform closed loop type spatial multiplexing transmission.
In another aspect, the invention relates to a wireless communication system, a wireless communication apparatus, and a wireless communication method, which perform beamforming by obtaining a channel matrix on the basis of training series transmitted from a receiver when a transmitter transmits a packet, and more particularly, to a wireless communication system, a wireless communication apparatus, and a wireless communication method, which perform beamforming using the training series transmitted from the transmitter to the receiver when a number of antennas of the transmitter, which is a beamformer, is smaller than that of the receiver, which is a beamformee.
2. Background Art
Wireless networks have attracted attention recently. A standard of wireless network may be IEEE (Institute of Electrical and Electronics Engineers) 802.11 or IEEE 802.15.
For example, IEEE 802.11a/g, a standard of wireless Local Area Network (LAN), employs an orthogonal frequency division multiplexing (OFDM) modulation method, which is a multi-carrier method. Because, in the OFDM modulation method, transmission data having orthogonal frequencies is distributed to a plurality of carriers and transmitted, the band of each carrier becomes narrow, spectrum efficiency is very high, and resistance to frequency-selective fading interference is strong.
In addition, IEEE 802.11a/g standard supports a modulation method for accomplishing a communication speed up to 54 Mbps. However, a next-generation wireless LAN standard requires a higher bit rate.
In order to realize a higher speed for wireless communications, multi-input multi-output (MIMO) communication has attracted attention. MIMO communication employs a plurality of antennas in a transmitter and in a receiver to realize spatially multiplexed streams. The transmitter performs spatial/temporal encoding and multiplexing of plural pieces of transmission data, and distributes and transmits the plural pieces of transmission data to N transmission antennas through channels, where N is a positive integer. The receiver performs spatial/temporal decoding on signals received by M reception antennas through the channels to obtain reception data without crosstalk between the streams (see, for example, JP-A-2002-44051, hereinafter referred to as Patent Document 1), where M is a positive integer. Ideally, spatial streams are formed corresponding to a fewer number of transmission and reception antennas (i.e. MIN[N, M]).
According to MIMO communication, a transmission capacity can be increased according to the number of antennas, and a communication speed can be improved without increasing frequency bands. Because spatial multiplexing is used, spectrum efficiency is high. MIMO communication uses channel characteristics and is different from a simple transmission/reception adaptive array. For example, in IEEE 802.11n, which is a standard extended from IEEE 802.11a/g, an OFDM_MIMO method using OFDM as the primary modulation is employed. Currently, IEEE 802.11n is standardized in Task Group n (TGn), in which a specification is established based on a specification established in Enhanced Wireless Consortium (EWC) formed in October, 2005.
In MIMO communication, in order to spatially divide a spatially multiplexed reception signal y into stream signals x, a channel matrix H may be acquired by any method and spatially multiplexed reception signal y may be spatially divided into a plurality of original streams using channel matrix H by a predetermined algorithm.
Channel matrix H is obtained by allowing a transmitter/receiver to transmit/receive existing training series, estimating channels by a difference between the actually received signal and the existing series, and arranging propagation channels in a matrix form according to a combination of transmission and reception antennas. When there are N transmission antennas and M reception antennas, the channel matrix is an M×N (row×column) matrix. Accordingly, the transmitter transmits N training series and the receiver acquires channel matrix H using the received training series.
A method for spatially dividing a reception signal is generally classified into an open loop type method, in which a receiver independently performs spatial division on the basis of channel matrix H, and a closed loop type method, in which a transmitter gives weight to transmission antenna on the basis of channel matrix H to perform adequate beamforming toward a receiver to form an ideal spatial orthogonal channel.
For an open loop type MIMO transmission method, there is a zero force (see, for example, A. Benjebbour, H. Murata, and S. Yoshida, “Performance comparison of ordered successive receivers for space-time transmission,” Proc. IEEE VTC Fall, vol. 4, pp. 2053-2057, Atlantic City, USA, September 2001, hereinafter referred to as Non-Patent Document 2) or a minimum mean square error (MMSE) (see, for example, “http://radio3.ee.uec.ac.jp/MIMO(IEICE_TS).pdf” (Oct. 24, 2003), hereinafter referred to as Non-Patent Document 3) The open loop type MIMO transmission method is a relatively simple algorithm for obtaining reception weight matrix W for spatially dividing the reception signal from channel matrix H, in which a feedback operation for sharing the channel information between the transmitter and the receiver is omitted, and the transmitter and the receiver independently perform spatial multiplexing transmission.
For an ideal closed loop type MIMO transmission method, a singular value decomposition (SVD)-MIMO method using SVD of channel matrix H is known (see, for example A. Benjebbour, H. Murata, and S. Yoshida, “Performance of iterative successive detection algorithm for space-time transmission,” Proc. IEEE VTC Spring, vol. 2, pp. 1287-1291, Rhodes, Greece, May 2001, hereinafter referred to as Non-Patent Document 1). In the SVD-MIMO transmission, a numerical matrix having channel information that uses antenna pairs as elements, that is, a channel information matrix H, is subjected to the singular value decomposition to obtain UDVH. A transmitter uses V in a transmission antenna weight matrix, and transmits a beamformed packet to a receiver. A receiver typically uses (UD)−1 as a reception antenna weight matrix. Here, D is a diagonal matrix having square roots of singular values λ1 corresponding to qualities of the spatial streams in diagonal elements (the subscript “i” indicates the i-th spatial stream) Singular values λi are the diagonal elements of diagonal matrix D in ascending order. Power ratio distribution or modulation method allocation is performed according to communication quality represented by the level of singular value with respect to the streams, such that a plurality of spatial orthogonal multiplexed propagation channels, which are logically independent, are realized. The receiver can extract a plurality of original signal series without crosstalk, and theoretically accomplish maximum performance.
In the closed loop type MIMO communication system, adequate beamforming is performed when the transmitter transmits a packet, but information on the channel information needs to be fed back from the receiver for receiving the packet.
For example, in EWC HT (High Throughput) MAC (Media Access Control) Specification Version V1.24, two kinds of procedures, namely, “implicit feedback” and “explicit feedback,” are defined as the procedure for feeding back the information on the channel matrix between the transmitter and the receiver.
For “implicit feedback,” the transmitter estimates a backward channel matrix from the receiver to the transmitter using training series transmitted from the receiver, and a forward channel matrix from the transmitter to the receiver is computed to perform beamforming under the assumption that bidirectional channel characteristics between the transmitter and the receiver are reciprocal. Calibration of an RF circuit in a communication system is performed such that the channel characteristics are reciprocal.
For “explicit feedback,” the receiver estimates a forward channel matrix from the transmitter to the receiver using training series transmitted from the transmitter, and returns a packet including the channel matrix as data to the transmitter. The transmitter performs beamforming using the received channel matrix. Alternatively, the receiver computes a transmission weight matrix for allowing the transmitter to perform beamforming from an estimation channel matrix, and returns a packet including the transmission weight matrix as the data to the transmitter. For explicit feedback, the channels may not be assumed to be reciprocal, because the weight matrix is computed on the basis of the estimated forward channel matrix.
In view of packet transmission, the transmitter is an initiator and the receiver is a terminator. However, in view of beamforming, the initiator for transmitting the packet is a beamformer and the terminator for receiving the beamformed packet is a beamformee. Communication from the beamformer to the beamformee is referred to as “forward,” and communication from the beamformee to the beamformer is referred to as “backward.”
For example, when an access point (AP) transmits a data frame to a client terminal (STA) as the beamformer, explicit feedback requires that the client terminal as the beamformee may only return the training series to the access point for beamforming.
A frame exchange procedure for transmitting the beamforming from the access point to the client terminal by implicit feedback will be described with reference to FIG. 8.
First, the access point requests the client terminal to transmit training series. According to the EWC MAC specification, a link adaptation control field (illustrated in FIG. 10) of an HT control field (illustrated in FIG. 9) of an MAC frame includes a training request bit TRQ. A value of 1 in training request bit TRQ corresponds to a transmission request of the training series.
The client terminal returns a sounding packet. The sounding packet includes the training series corresponding to N transmission antennas of the access point and M reception antennas of the client terminal. The access point can estimate an N×M backward channel matrix when receiving the sounding packet. The access point computes a forward transmission weight matrix for beamforming using the SVD, an Eigen value decomposition (EVD) method, or other matrix decomposition methods, and multiplies transmission signal from the antennas by the transmission weight matrix, such that the beamformed packet can be sent to the client terminal. By beamforming, the client terminal may perform wireless communication at a high transmission rate, even if the client terminal is located at a place where it is difficult to receive the packet in the past.
Subsequently, an operation for allowing the beamformer to perform beamforming using the training series from the beamformee according to implicit feedback will be described with reference to FIG. 11. In FIG. 11, an STA-A having three antennas is a beamformer and an STA-B having two antennas is a beamformee. Hereinafter, a subscript AB indicates forward transmission from STA-A to STA-B and a subscript BA indicates backward transmission from STA-B to STA-A. A numerical subscript corresponds to an antenna number of the corresponding terminal. It is assumed that the channels between STA-A and STA-B are reciprocal. Accordingly, a backward channel matrix HBA becomes a transposed forward channel matrix HAB (i.e. HBA=HABt)
The training series transmitted from the antennas of STA-B are (tBA1, tBA2), and the signals received by the antennas of STA-A through a channel HBA are (rBA1, rBA2, rBA3). The following equation (1) is obtained.
                              (                                                                      r                                      BA                    ⁢                                                                                  ⁢                    1                                                                                                                        r                                      BA                    ⁢                                                                                  ⁢                    2                                                                                                                        r                                      BA                    ⁢                                                                                  ⁢                    3                                                                                )                =                              H            BA                    ⁡                      (                                                                                t                                          BA                      ⁢                                                                                          ⁢                      1                                                                                                                                        t                                          BA                      ⁢                                                                                          ⁢                      2                                                                                            )                                              (        1        )            
where, channel matrix HBA is a 3×2 matrix expressed by equation (2). Here, hij is a channel characteristic value of the j-th antenna of STA-B with respect to the i-th antenna of STA-A.
                              H          BA                =                  (                                                                      h                  11                                                                              h                  12                                                                                                      h                  21                                                                              h                  22                                                                                                      h                  31                                                                              h                  32                                                              )                                    (        2        )            
When channel matrix HBA is subjected to singular value decomposition, equation (3) is obtained. Here, UBA is a matrix having an inherent normalized vector of HBAHBAH, VBA is an inherent normalized vector of HBAHHBA and DBA is a diagonal matrix having a square root of an inherent vector of HBAHBAH or HBAHHBA as diagonal elements. In addition, UBA and VBA are unitary matrices, namely complex conjugate of a transposed matrix becomes the inverse of the matrix.HBA=UBADBAVBAH  (3)
The transmission weight matrix necessary for performing beamforming of the frame transmitted from STA-A to STA-B is matrix VAB obtained by performing the singular value decomposition with respect to forward channel matrix HAB. Here, because the channels between STA-A and STA-B are reciprocal and backward channel matrix HBA becomes the transposed matrix of forward channel matrix HAB, the singular value decomposition of channel matrix HAB is computed in equation (4).
                                                                        H                AB                            =                                                U                  AB                                ⁢                                  D                  AB                                ⁢                                  V                  AB                  H                                                                                                        =                                                V                  BA                  *                                ⁢                                  D                  BA                                ⁢                                  U                  BA                  T                                                                                        (        4        )            
When the reciprocity of channels is used, a desired transmission weight matrix VAB is expressed by equation (5).
                                                                        V                AB                            =                                                (                                      V                    AB                    H                                    )                                H                                                                                        =                                                (                                      U                    BA                    T                                    )                                H                                                                                        =                                                (                                                            (                                              U                        BA                        T                                            )                                        T                                    )                                *                                                                                        =                              U                BA                *                                                                        (        5        )            
That is, it is possible to perform beamforming using the complex conjugate of matrix UBA obtained by performing the singular value decomposition with respect to the channel matrix estimated on the basis of the training signal from STA-B.
If the transmission signal of STA-A is x and a reception signal from STA-B is y, reception signal y becomes HABx (i.e. y=HABx) in a case where the beamforming is not performed (un-steered). If the beamforming are performed by the transmission weight matrix VAB (steered), reception signal y is obtained in equation (6).
                                                        y              =                                                                    H                    AB                                    ⁢                                      V                    AB                                    ⁢                  x                                =                                                                            (                                                                        U                          AB                                                ⁢                                                  D                          AB                                                ⁢                                                  V                          AB                          H                                                                    )                                        ·                                          V                      AB                                                        ⁢                  x                                                                                                        =                                                U                  AB                                ⁢                                  D                  AB                                ⁢                x                                                                        (        6        )            
Accordingly, STA-B can perform spatial division of the original stream by multiplying the reception signals by DAB−UABH as a reception weight.
Subsequently, the explicit feedback will be described. In explicit feedback, the beamformer can receive the explicit feedback of the estimation channel matrix from the beamformee. The format of the feedback of the estimation channel matrix is generally classified into a case where an MIMO channel coefficient is sent, and a case where transmission weight matrix V for beamforming calculated by the beamformee is sent. The format of the former is called channel state information (CSI). In this case, the beamformer needs to compute transmission weight matrix V for beamforming by constructing channel matrix H from the received CSI and by performing the singular value decomposition. The latter is generally classified into a case where transmission weight matrix V for beamforming is sent in an uncompressed format, and a case where transmission weight matrix V for beamforming is sent in a compressed format.
FIG. 12 shows a frame exchange procedure for transmitting beamforming from the access point to the client terminal by explicit feedback.
This procedure is initiated by the access point which sends the sounding packet including a CSI feedback request.
The client terminal estimates the channel matrix based on the sounding packet and collects the CSI. The CSI data is included in the packet as a CSI feedback (CFB) and returned to the access point.
The access point computes the transmission weight matrix for beamforming from the received CFB and multiplies the transmission signal by the transmission weight matrix to transmit the beamformed packet to the client terminal. Even if the access point is located in a place where wireless communication was difficult to achieve in the past, wireless communication can be accomplished at a high transmission rate by beamforming.
According to implicit feedback described above, reduced burden on the beamformee due to the feedback allows the access point (AP) to transmit a data frame to client terminal STA as beamformer. However, in this case, the terminal, which is the beamformer, computes the transmission weight matrix for beamforming by performing the singular value decomposition or other calculation method with respect to the channel matrix estimated from the received training series. This calculation, however, has a heavy processing load, and the processing load increases depending on the increase of the number of streams of the training series transmitted from the beamformee.
In an example shown in FIG. 11, STA-A includes three antennas (N=3), and STA-B includes two antennas (M=2). Because there are more antennas in STA-A than in STA-B, no problem is caused in the processing capability for beamforming. This is because STA-A is designed to include the processing capability corresponding to N of its own streams; the training series of the spatial streams of N or less are divided; an N×M channel matrix is constructed from the divided training series; and the matrix for beamforming is computed based on the N×M channel matrix.
However, for N<M, that is, the number of antennas of the beamformee is larger than that of the beamformer, problems may be caused because the beamformer does not include the processing capability which exceeds the number of its own spatial streams. When STA-A can process only N streams, which is equal to the number of antennas, M stream trainings may not be divided or the matrix for beamforming may not be obtained from the N×M estimation channel matrix.
In order to solve such problems without deteriorating the beamforming characteristics, it may be considered that a channel estimation maximum dimension Mmax corresponding to a rated maximum number of antennas is given to STA-A as the beamformer (for example, if it is based on the IEEE specification, Mmax=4) and the processing capability for computing the transmission weigh matrix for beamforming is given to the obtained N×Mmax estimation channel matrix.
For example, when STA-A includes two antennas (i.e. N=2) and the rated maximum number of antennas is Mmax=4, STA-A can compute only a 2×2 matrix for communication with the terminal having the same number of antennas, but needs to compute a 2×4 matrix. In this case, calculation or processing circuit needs to be doubled, which renders it difficult to reduce the size and the cost of the communication apparatus.